Also in web ads, in some cases, you need to use a third-party connector for data transfer. For example, when the user did not interact with the site, but simply viewed the ad. This connector can be created manually or you can use services for automatization and optimization of ad campaigns, where such integration has already been added.
Using predictive analytics on web has other peculiarities:
- Not all data from sources can be integrated into Google Analytics —if this data is lostthe model becomes inaccurate.
- Google will stop using third-party cookies to track user activity on the Internet by the end of 2023. Without collecting personal data, it’s not possible to see about 60% of the traffic and that will complicate model learning.
What predictive analytics give from marketing perspective
1. Users are attracted based on their future payback
With the help of predictive analytics, you can estimate what the user’s payback will be, how much profit users will bring and how soon. Based on this information, you can attract users with a high pLTV and calculate the amount of money that is necessary for the advertisers to attract such users.
Let’s look at an example.To attract one user, the advertiser paid CPI $10, and for the second one he paid $5. He deliberately pays more money for the first user, knowing that his LTV will be higher and he will bring him more profit.
2. Optimization objective is moved to the metric important for business
The most common objective for a business is revenue. To understand whether a user will bring money, in classic marketing you need to wait for at least a month.
In predictive marketing, by analyzing the primary behavior of each specific user it is possible to estimate the value of the long-term metric that is important for business.
Let’s look at two examples of how to attract profitable customers.
